Prediction of survival,immune microenvironment,and medication in patients with esophageal squamous cell carcinoma using a risk scoring model based on MAPK signaling pathway related genes
Objective:To construct a prognostic model based on mitogen-activated protein kinase(MAPK)signa-ling pathway related genes(MRGs)to help improve the prognosis of esophageal squamous cell carcinoma(ESCC)patients.Methods:Transcriptional data and clinical information of ESCC patients were obtained from the the Canc-er Genome Atlas(TCGA),and MRGs were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG)database.Cluster analysis was performed on patients based on ESCC genes related to survival in MRGs.Based on the differential genes of these two clusters,Cox regression analysis was conducted to screen prognosis genes and construct a risk model.Gene ontology(GO),KEGG analysis and single sample Gene Set Enrichment Analysis(ssG-SEA)were performed between high-and low-risk groups based on the prognostic model.The CellMiner database was utilized to search for drugs that may be related to model genes.Results:13 genes were screened to construct a prognosis model via regression analysis.The prognosis model showed stable and accurate predictive ability in the TCGA and Gene Expression Omnibus(GEO).The GO and KEGG analysis results showed significant differences in biological functions and pathways such as leukocyte mediated immunity and cell adhesion molecules between the high-and low-risk groups based on this model.ssGSEA found that patients in the high-risk group had significantly higher levels of immune cell infiltration and most immune functions than those in the low-risk group.Conclusion:We have developed a prognostic model with good and reliable predictive ability,which may have guiding signifi-cance for the prognosis and treatment research of ESCC.
esophageal squamous cell carcinomamitogen-activated protein kinase signaling pathwayprognosisthe Cancer Genome Atlas databaseimmune
万方数据
维普
